Target-tracking in Flir Imagery Using Mean-shift and Global Motion Compensation
نویسندگان
چکیده
In this paper, we present a new approach for tracking targets in forward-looking infrared (FLIR) imagery taken from an airborne, moving platform. Our tracking approach uses the target intensity and the Gabor response distributions and computes a likelihood measure between the candidate and the model distributions by evaluating the Mean Shift Vector. When the Mean Shift Vector based tracker fails to locate the target due to large ego motion, we compensate the ego motion using a multi-resolution scheme, which employs the Gabor responses of two consecutive frames, and assumes a pseudo-perspective motion model. We present the experiments performed on an AMCOM FLIR dataset of the proposed tracking algorithm.
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